The American Rehabilitation Association recently (1994) reported that the average hospital operating cost per inpatient medical rehabilitation day for Medicare and non-Medicare patients was $561.00. The cost per day of inpatient medical rehabilitation increased approximately 40% from 1986 to 1992. National data currently exist on length of stay (LOS) and other variables related to initial inpatient rehabilitation. No information, however, has been published examining the rate and cost of rehospitalization for patients following discharge from inpatient medical rehabilitation. The purpose of this investigation is to systematically examine a large sample of community based persons who received inpatient medical rehabilitation. Follow-up data collected by the National Followup Services will be analyzed. The National Followup Services collects follow-up information on patients who received inpatient medical rehabilitation at facilities that provide data to the Uniform Data System for Medical Rehabilitation (UDSmr). The National Followup Services data base contains approximately 35,000 records for persons living in the U.S. The data base includes demographic variables, medical history, and Functional Independence Measure ratings for each subject. National Followup Services data will be compared to records in the UDSmr data base to determine the comparability of patients in the follow-up data set. Elements of the National Followup Services data base will be examined with particular attention to the variable of rehospitalization. Rehospitalization will be investigated for various impairment groups and age categories. Discriminant function analysis will be used to examine the relationship between demographic characteristics (age, sex, etc.), medical history, and FIM ratings and incidents of rehospitalization. The results of Discriminant function analysis will be compared to predictions of rehospitalization obtained using neural network simulation software. Discriminant function analysis and neural network analysis will be used to develop prediction models to determine characteristics and patterns of variables associated with hospital readmission for different impairment groups. The development of prediction models for rehospitalization of persons receiving medical rehabilitation will improve the effective use of future resources.